Lifting wavelet de-noising for SINS alignment
Yuhao Liu, Xinsheng Huang, Dongxue Yue · 2008
Considering inertial sensors measurements (ISM) containing many stochastic noises, the application of lifting wavelet transform(LWT) algorithm in the de-noising of ISM is put forward for Strapdown Inertial Navigation System(SINS) alignment. First, the LWT algorithm is introduced and applied into the de-noising of ISM. Then, the coarse alignment model and nonlinear fine alignment model under large heading uncertainty are built up. Finally, with the de-noised measurements, the results of SINS coarse alignment and fine alignment verify the effect of the LWT de-noising algorithm. Results show that LWT algorithm is effective in the de-noising of ISM, and also it can improve the convergence rate and precision of SINS alignment.